جست‌وجوی استاد و پژوهشگر

Milad Toutounchianمشاهده پروفایل

استادیار

• Machine Learning
• Deep Learning
• Data Science
• +۳ مورد دیگر

Milad Toutounchian serves as an Assistant Teaching Professor within the Department of Information Science at Drexel University's College of Computing & Informatics (CCI). Prior to joining Drexel, he gained industry experience as a data scientist, lead data science instructor at Make School, and mentor at Springboard's Data Science Career Track. His professional background bridges academic theory with practical industry applications. Dr. Toutounchian's educational background includes: PhD in Electrical Engineering from Simon Fraser University BSc in Telecommunication from Sharif University of Technology His primary research interests lie in applied machine learning and deep learning, with a focus on real-world problem solving. Recent work explores AI-driven medical diagnostics, particularly in breast cancer detection using multi-scale and multi-view transformer frameworks. Earlier research addressed signal processing challenges in wireless communications, including beamforming for MIMO systems and cognitive radio networks. This evolution highlights a transition from communications engineering to data science applications in healthcare. Analysis of his publication history reveals a clear shift in research focus. From 2010 to 2016, his work centered on wireless communications and signal processing, contributing to MIMO systems and beamforming techniques. Since 2023, he has pivoted toward healthcare applications of AI, developing deep learning frameworks for human-centric breast cancer diagnostics. This trajectory demonstrates adaptability across technical domains while maintaining core expertise in machine learning methodologies. No scientific awards or major honors were documented in the available information. While his biography notes teaching responsibilities and industry mentoring experience, specific details about graduate student advising or research grants were not provided in the source material. No information regarding laboratory affiliations, research teams, or collaborative groups was mentioned.

• Computational Biology
• Cardiac Electrophysiology
• Systems Biology
• +۴ مورد دیگر

David Gavaghan is a Professor of Computational Biology at the University of Oxford's Department of Computer Science, within the Mathematical, Physical and Life Sciences Division. He leads the Computational Biology Group and has held roles including Director of Graduate Studies in the Mathematical, Physical and Life Sciences Division and Chair of the Department's Equality and Diversity Committee. His research focuses on computational modeling of biomedical systems, particularly cardiac electrophysiology, tumor development, and electrochemical techniques. He has supervised over 30 PhD students and established the Life Science Interface Doctoral Training Programme, funded by £60 million in grants. Notable projects include the Chaste computational library and collaborations with industry partners like Microsoft Research and GSK. Research interests include interdisciplinary applications of mathematical and computational methods to biomedicine, with a focus on cardiac modeling, systems biology, and high-performance computing. He chairs the Chaste Users' Mailing List and has contributed to initiatives like the 2020 Science programme for computational natural scientists. His work emphasizes practical solutions for scientific challenges and has led to innovations in computational infrastructure and collaborative research frameworks such as the Virtual Physiological Human Toolkit. Professional activities include leadership in doctoral training, grants management, and gender equality initiatives. His contributions span academic and industrial collaborations, emphasizing the translation of computational models into real-world biomedical applications.

Hai Huyen Heidi Damمشاهده پروفایل

مدرس ارشد

• Digital Signal Processing
• Wireless Communications
• Channel Equalisation
• +۴ مورد دیگر

Dr. Hai Huyen Heidi Dam is a Senior Lecturer at Curtin University's School of Electrical Engineering, Computer, and Mathematical Sciences (EECMS), under the Faculty of Science and Engineering. Her research focuses on digital signal processing, wireless communications, channel equalization, and digital filter design and optimization. She holds a BSc (Hons) and PhD (Curtin) in related fields. Her work spans theoretical and applied signal processing, including speech enhancement, blind signal separation, and robust beamforming. Key contributions include optimized filter design, multiuser MIMO systems, and adaptive feedback control in hearing aids. Dr. Dam has published extensively in journals like IEEE Transactions on Signal Processing and Circuits Systems and Signal Processing. Her research trends emphasize optimization algorithms, real-time signal processing, and practical implementations in acoustics and communications. Collaborations with industry and academia highlight her contributions to noise reduction, microphone array systems, and sensor technologies. Active in academic service, she contributes to the Office of the Provost at Curtin's Perth campus. Her lab and team focus on advancing signal processing solutions for real-world challenges in audio, communications, and control systems.

Rui Zhangمشاهده پروفایل

استادیار

• Statistical Signal Processing
• Optical and Wireless Communications
• Integrated Communication and Sensing
• +۵ مورد دیگر

Rui Zhang is an Assistant Professor in the Department of Electrical Engineering at the School of Engineering and Applied Sciences , State University of New York at Buffalo. Her research focuses on next-generation communication systems , including fiber-wireless integration , statistical signal processing , integrated communication and sensing , and optical wireless networking . PhD, School of Electrical and Computer Engineering, Georgia Institute of Technology, 2022 BS in Electrical Engineering and BA in Economics, Peking University, 2017 She has made significant contributions to 6G wireless research and hybrid optical-wireless networks . Her recent publications explore integrated communication-sensing systems , high-capacity data center links , and nonlinear signal equalization . Notably, her work on OFDM reference signal design and self-homodyne coherent systems has received recognition at top conferences. Rui Zhang has been honored with the prestigious 2022 Marconi Young Scholar Award and received the Top-scored Paper Award at OFC 2022. She actively mentors students, currently advising Zijun Wang , a PhD candidate. Her industry experience includes a Staff Engineer role at MediaTek USA (2022–2023), where she worked on 6G wireless systems.

• Digital communication
• Embedded systems
• Ultrasonics
• +۳ مورد دیگر

Kyle Wilt is a Senior Lecturer in the Department of Electrical, Computer, and Systems Engineering at Rensselaer Polytechnic Institute (RPI). His research focuses on digital communication, embedded systems, and ultrasonics, with a particular emphasis on wireless ultrasonic power transmission, piezoelectric transducer design, and acoustic wave theory. He has contributed to advancements in through-wall communication systems, sensor networks, and acoustic-electric channel modeling. Wilt's work explores ultrasonic communication through challenging mediums like reinforced concrete and cylindrical pipes, addressing applications ranging from low-power sensor networks to high-rate data transmission. His research integrates hardware design, signal processing, and material science to solve real-world communication challenges in constrained environments. His publications span topics such as MIMO-OFDM systems, resource allocation in multichannel networks, and low-power communication protocols. Despite no awards explicitly mentioned, his contributions reflect a commitment to practical engineering solutions. No advising or grant information is provided in the text. Wilt’s expertise in acoustic fiber technologies and transducer integration demonstrates his role in advancing smart infrastructure and system-of-systems monitoring. His research bridges theoretical models with applied engineering, addressing both academic and industry-relevant problems.

Ali Abdiمشاهده پروفایل

استاد

• Underwater Acoustics
• Signal Processing
• Wireless Communications
• +۲ مورد دیگر

Ali Abdi is a Professor of Electrical and Computer Engineering at the New Jersey Institute of Technology. He holds a Ph.D. in Electrical Engineering from the University of Minnesota-Twin Cities (2001), an M.S. from the University of Tehran (1996), and a B.S. from Iran University of Science and Technology (1991). His research spans underwater acoustic communications, signal processing, wireless systems, and neural network modeling. Recent work focuses on multichannel signal detection, MIMO systems, and molecular network analysis. His publications demonstrate consistent innovation in signal processing theory and experimental validation for underwater and wireless systems, with emerging applications in molecular communication and decision modeling.

Daniel Ka Chun Soمشاهده پروفایل

استاد

• Green Communications
• Beyond 5G/6G Networks
• Non-orthogonal Multiple Access
• +۹ مورد دیگر

Daniel Ka Chun So is a Professor of Communication Engineering in the Department of Electrical & Electronics Engineering at the University of Manchester. He joined the university in 2003 and holds a PhD from Hong Kong University of Science of Technology (2003) and a BEng from University of Auckland (1996). His industrial experience includes senior software engineering roles at Orion Systems. Research focuses on next-generation wireless technologies including green communications, 6G networks, machine learning applications, and network optimization. Key areas include: Energy-efficient wireless systems Non-orthogonal multiple access (NOMA) Reconfigurable intelligent surfaces Massive MIMO and D2D communications Recent publications demonstrate strong emphasis on federated learning optimization, cell-free massive MIMO, and cache-enabled D2D communications, reflecting cutting-edge work in wireless network efficiency. Awards include: Scottish Power Power Learning Award Two-time recipient of UMIST Electrical & Electronic Engineering Prize Extensive PhD supervision includes 19 current and former students working on NOMA systems, edge computing, and 6G optimization. Leadership roles include Director of Postgraduate Taught programs and Teaching Enhancement Lead.

• Underwater Acoustics
• Acoustic Remote Sensing
• Geoacoustic Modeling
• +۵ مورد دیگر

Hefeng Dong is a Professor at the Department of Electronic Systems (IES) within the Faculty of Information Technology and Electrical Engineering at NTNU. Her research focuses on underwater acoustics, acoustic remote sensing, seismic modeling, and environmental impact assessment of low-frequency sound. She has held academic positions since 2002 and has collaborated internationally, including stays at the University of Victoria (Canada) and University of Delaware (USA). Education: BSc in Physics (1983), Northeastern Normal University, China MSc in Theoretical Physics (1986), Northeastern Normal University, China PhD in Geoacoustics (1994), Jilin University, China Research Interests: Her work spans underwater acoustic communication, geoacoustic inversion, seismic wave analysis, and environmental monitoring using distributed acoustic sensing (DAS). She explores applications such as marine life impact assessment, fiber-optic cable utilization for geophysical sensing, and machine learning-based signal processing. Recent Research Trends: Recent publications emphasize integration of machine learning (e.g., deep reinforcement learning for shear wave velocity estimation) and novel sensor technologies (e.g., DAS for acoustic communication and seismic monitoring). Her work addresses challenges in multipath signal propagation, passive sensing for microseisms, and environmental noise analysis. Grants & Advising: Advises graduate students on projects involving acoustic source localization, DAS applications, and signal processing. Collaborates with institutions like SINTEF Petroleum and international universities on geophysical and acoustic sensor projects. Labs/Teams: Affiliated with the Acoustics Group at IES, focusing on experimental and theoretical advancements in underwater acoustics and geophysical sensing.

• Signal Processing
• Communications Engineering
• Power Line Communications
• +۶ مورد دیگر

Fernando Cruz Roldán is a **Professor** at the Universidad de Alcalá (UAH) , affiliated with the Department of Signal Theory and Communications . He holds a PhD from UAH with a thesis on filter bank design for minimal amplitude distortion. His research focuses on signal processing, communications engineering, and biomedical applications. Key areas include OFDM systems , power line communications , filter design , and machine learning in healthcare . His work spans theoretical advancements in multicarrier modulation (e.g., DCT-based systems) and practical applications like ECG/EEG signal compression and T-wave alternans detection. Recent contributions address AI-driven solutions in education and medical diagnostics. He has published extensively on topics such as channel estimation, intersymbol interference mitigation, and biomedical signal analysis. Notable achievements include pioneering work on α-spline digital filters and innovative approaches to signal processing in noisy environments. His research bridges theoretical signal theory with real-world applications in telecommunications and healthcare.

Nadhir Ben Rachedمشاهده پروفایل

مدرس

• Stochastic Mathematical Modelling
• Stochastic Numerics
• Monte Carlo Methods
• +۱۱ مورد دیگر

Dr Nadhir Ben Rached is a Lecturer in Statistics at the School of Mathematics within the Faculty of Engineering and Physical Sciences at the University of Leeds. His academic journey includes a PhD in Applied Mathematics and Computational Science from KAUST (2018), a Master's degree from KAUST (2013), and a Diplôme d’Ingénieur from École Polytechnique de Tunisie (2012). Education: PhD, Applied Mathematics and Computational Science, KAUST (2018) MSc, Applied Mathematics and Computational Science, KAUST (2013) BSc, Polytechnic Engineering, École Polytechnique de Tunisie (2012) Nadhir’s research centers on stochastic mathematical modelling and stochastic numerics , focusing on high-dimensional systems, rare events, and low regularity challenges. His work develops Monte Carlo methods and variance reduction techniques , particularly Multilevel Monte Carlo (MLMC) and Multi-Index Monte Carlo (MIMC) , to address computational inefficiencies in simulations. Applications of his research span computational finance , wireless communications , biological systems , and supply chain optimization . Current projects include stochastic optimal control (SOC) for power procurement in renewable-powered wireless networks and inventory management under uncertain demand. He designs scalable algorithms for high-dimensional stochastic systems , emphasizing practical decision-making frameworks. From October 2022 to October 2024, Nadhir was 50% seconded to the UK Met Office, fostering collaborations in weather and climate science. He is an Associate Editor for Statistics and Computing and a member of research groups including Modern Applied Statistics, Probability and Financial Mathematics, and Statistical Methodology.

• Signal Processing
• Wireless Communications
• Ultra-Wideband Localization
• +۳ مورد دیگر

Eva María Arias de Reyna Domínguez serves as a Full Professor in the Department of Signal Theory and Communications at the University of Seville. Her research is centered within the Signal Processing and Communications research group (TIC-155), where she has led numerous national and international projects focused on advanced signal processing techniques for wireless communications and localization systems. Her research interests span Signal Processing , Wireless Communications , and Ultra-Wideband Localization , with particular expertise in Expectation Propagation algorithms, UWB signal processing, and crowd-based learning for IoT applications. Her work bridges theoretical signal processing with practical implementations in digital communications and indoor positioning systems. Analysis of her 15 most recent publications reveals a consistent focus on Expectation Propagation techniques for digital communications (constituting 40% of recent work), UWB localization algorithms (30%), and channel equalization methods (20%). Her research demonstrates a progression from fundamental signal processing algorithms toward IoT-integrated spatial field estimation and machine learning applications. She has advised doctoral student Irene Santos Velazquez (2018 thesis on Expectation Propagation for digital communications) and participated in significant research projects including ATENEA (Artificial Intelligence for Art Fabric Analysis), Finite-Length Iterative Decoding, and multiple national grants under Spain's TEC and CSD programs. Her laboratory work centers on the Signal Processing and Communications research group, which has received continuous consolidation funding from 2005-2017.

• Signal Processing
• Communications Engineering
• Artificial Intelligence
• +۲ مورد دیگر

Francisco José Simois Tirado is an Assistant Professor in the Department of Signal Theory and Communications at the University of Seville. He actively participates in multiple research projects funded by the State Research Agency (AEI) and the Andalusian Government, including "IAREPRO II" (AI for assisted reproduction), "MISION ALPHA" (CubeSat development), and IoT-based structural health monitoring. His work bridges signal processing, communications engineering, and interdisciplinary applications in art conservation and agriculture. His research interests center on signal processing techniques (Fourier transforms, convolutions, spectral analysis) and communications systems (OFDM, channel estimation, precoding). Recently, he has extended these methods to art canvas analysis and dairy farm biosecurity, showcasing adaptability across diverse fields while maintaining core signal processing expertise. An analysis of his publications reveals a trajectory from foundational communications research to impactful interdisciplinary applications. His recent work applies signal processing to art authentication and veterinary science, demonstrating the versatility of his core methodologies in solving real-world problems beyond traditional engineering domains. Dr. Simois Tirado has contributed to over 15 research projects since 2002, spanning wireless communications, IoT, and AI applications. He is a long-standing member of Research Group TIC-155, which has received multiple consolidation incentives from the Andalusian Government, reflecting sustained research excellence. He is affiliated with the Signal Processing and Communications Research Group at the University of Seville, a team focused on advancing signal processing theory and its applications in communications, biomedical engineering, and cultural heritage preservation.

Julien Guillodمشاهده پروفایل

دانشیار

• Fluid Dynamics
• Navier–Stokes Equations
• Asymptotic Expansions
• +۵ مورد دیگر

Julien Guillod is an Associate Professor of Applied Mathematics at Sorbonne Université in Paris, with a part-time affiliation at ENS Paris and membership in the ANGE team at Inria . He holds a PhD in Physics from Université de Genève (2015) and has held postdoctoral positions at institutions including Princeton University and Brown University. Research Interests : Fluid dynamics (Navier–Stokes equations, asymptotic behavior) Nonlinear partial differential equations Numerical methods for time-dependent PDEs Python programming applications in mathematics Selected Recent Publications : 2024: Long-time behavior of the Stokes-transport system in a channel 2024: Existence and uniqueness for plane stationary Navier–Stokes flows 2023: Hyperbolicity of semi-Lagrangian formulations for Euler systems 2023: Nonlinear stability at the Eckhaus boundary 2022: Generalized scale-invariant solutions to Navier–Stokes equations Teaching & Responsibilities : Responsible for the Python Programming for Mathematics teaching unit (200 students, 12-14 teachers) since 2018 Co-organizer of the Paris seminar on nonlinear analysis and PDEs since 2019 Equality and anti-discrimination referent at Sorbonne Université since 2021 Developed several open-source projects including Django-based inventory systems and exam management tools

Håkan Johanssonمشاهده پروفایل

استاد

• Signal Processing
• Communications Engineering
• Digital Filter Design
• +۳ مورد دیگر

Håkan Johansson is a Professor at the Department of Electrical Engineering (ISY) at Linköping University, Sweden, affiliated with the Division of Communication Systems (KS). This division conducts research and education in communications engineering, statistical signal processing, and network science, emphasizing strong industrial collaborations and practical research applications. His research spans Signal Processing , Communications Engineering , and Digital Filter Design , focusing on low-complexity and reconfigurable solutions for communication systems. Key areas include power amplifier linearization, advanced sampling techniques, and equalization algorithms for 5G/6G and massive MIMO systems, with strong emphasis on implementation efficiency and real-world applicability. Recent publications (2024-2025) reveal a concentrated effort on energy-efficient signal processing for next-generation wireless infrastructure. Dominant themes include linearization of power amplifiers in multi-antenna systems, reconstruction of complex signals from nonuniform sampling, and machine learning integration for UAV communications, reflecting industry-driven priorities for 6G development. No scientific awards were documented in the provided materials. Professor Johansson operates within a robust research ecosystem at ISY, supervising PhD students in the Communication Systems division alongside colleagues like Erik G. Larsson (Head of Division). While specific grant details are absent, his extensive publication record indicates sustained funding for high-impact telecommunications research. He contributes to Linköping University's Communication Systems division, a collaborative hub bridging theoretical signal processing with industrial applications. The team specializes in end-to-end communication solutions from algorithm design to hardware implementation, maintaining strong ties with Sweden's telecommunications sector for rapid technology transfer.

• Signal Processing
• Communication Systems
• Machine Learning algorithms and systems
• +۷ مورد دیگر

Andrew C. Singer is a Professor at the University of Illinois at Urbana-Champaign , with joint appointments in the College of Engineering (Electrical and Computer Engineering, Industrial and Enterprise Systems Engineering) and the College of Business (Business Administration). Since 1998, he has held roles including the Fox Family Endowed Professorship , Associate Dean for Innovation and Entrepreneurship (2018–present), and Director of the Technology Entrepreneur Center (2005–2017). He co-founded Intersymbol Communications, Inc. (2000, acquired by Finisar) and OceanComm (2015, underwater video communication). Education: Ph.D. in Electrical Engineering and Computer Science, MIT (1996). Research Interests span statistical signal processing , acoustic communication systems , machine learning , and low-power VLSI design , with applications in underwater acoustics, through-tissue communication, and augmented listening. His work integrates theoretical signal processing with practical hardware implementations. Recent Publications focus on acoustic communication under nonlinear conditions , low-complexity ADC design , and biomedical applications of signal processing . Articles from 2023–2020 highlight innovations in underwater navigation, face mask acoustics, and subsurface data transmission. Scientific Awards include: Hughes Aircraft Masters Fellowship Harold L. Hazen Memorial Award (1991) NSF CAREER Award (2000) Xerox Outstanding Faculty Award (2001) IEEE Fellow IEEE Signal Processing Society Distinguished Lecturer (2014) Best Paper Awards (2006, 2008) Leadership roles include Associate Editor for IEEE Transactions on Signal Processing and service on the MIT Educational Council . He directs the Coordinated Science Lab and advises on expert witness cases in audio and communication industries.